The present invention relates generally to signal processing, and more specifically to signal processing for inlet debris monitoring systems for gas turbine engines.
Gas turbine engines draw in and compress environmental air. Aircraft gas turbines may operate in a wide range of environments, including environments wherein environmental air contains debris particulates, such as sand or ice, which can be harmful to turbine components.
Gas turbine engines for aircraft commonly include an inlet debris monitoring system (IDMS) which monitors ingestion of charge-carrying debris, and notifies pilots or updates a maintenance log in the event of discrete debris ingestion. Conventional IDMSs include electrostatic sensors which inductively sense the passage of charged particles, and produce sensor signals proportional to the magnitude of charge on ingested debris. These sensors can take several forms, such as buttons or rings of conductive material within or surrounding turbine air passages. Signals from these sensors are conventionally digitized and analyzed in the time domain to determine when debris events occur, how long debris events last, and the approximate overall rate of debris flow. Similar debris monitoring systems have conventionally been used to monitor debris both in turbine inlets and outlets. Conventional signal processing techniques are not capable of characterizing flow of small particulates which cannot be discretely sensed. While discrete debris ingestion produces relatively sharp time-domain signal peaks corresponding to each ingested debris piece, flow of smaller particulates such as sand or dust produces a broad band debris sensor signal. Conventional signal analysis systems and methods cannot reliably characterize the flow rate and composition of ingested particulate material, including for the purposes of damage estimation and prognosis.